The present invention relates generally to methods and systems for detecting agents in a bulk sample that can include one or more background constituents, and more particularly, for detecting bio-aerosol warfare agents.
The detection of bio-aerosol warfare agents in the presence of either indoor or outdoor backgrounds is a difficult problem. Natural backgrounds are variable and can simultaneously include multiple constituents. The variation of each constituent may be larger than the concentration level of an agent whose detection is desired. The detection problems can be further exacerbated by the presence of spikes in measurement data of a naturally-occurring background, which may be an order of magnitude larger than the contribution of the normal quiescent background. Such spikes may last for minutes and may exhibit large variations in particle count.
The detection of other important agents share some of the difficulties associated with the detection of bioaerosols. For example, chemical warfare agents may need to be detected in the presence of industrial cleaners or insecticides. Nuclear materials may be hidden by background radiation from rocks and cements, as well as by residual radiation from medical treatment or radiation from shipments of medical equipment. Signatures of explosives traces can be mimicked by foods preserved with nitrates as well as by legitimate shipments of fertilizers. Detection of pollutants and contaminants share the same problems as detection of biological, chemical, and radiological warfare agents. A solution to all of these problems requires the ability to detect low levels of agents in an ambient environment. The detection sensitivity can be increased by concentrating the sample to be analyzed, but at the risk of having both large amounts of background and small amounts of agent in the same sample. Further, simulants for a variety of agents, such as those mentioned above, are often used for detector development and testing. Thus, the detection of simulants is also an important problem requiring solution.
Some workers in the field have attempted to solve the problem of detecting low levels of agents against an ambient background by finding signatures that are unique to the agents whose detection is desired. This normally requires that signatures of agents and background constituents be unique and non-overlapping. This approach may work with signatures that have many very narrow features, such as those typically exhibited by LIBS (Laser Induced Breakdown Spectroscopy), Raman spectra, and FTIR (Fourier Transform Infrared) spectra. However, it is not suitable for signatures that have broad features, such as UV-induced fluorescence spectra and lifetime measurements, x-ray fluorescence spectra, and terahertz (THz) spectra. Hence, this conventional approach has the disadvantage that it limits the detection techniques that can be used to solve a given agent detection problem.
Another conventional method for detecting agents utilizes single particle flow-through systems, such as BAWS (Biological-Agent Warning Sensor) to make a small number of simultaneous measurements, a single particle at a time. Each particle could be classified based on this small number of measurements, and a histogram of particle locations in measurement space could be built up over time.
However, single particle flow-through systems have several disadvantages. First, the signal from a single particle is small. Expensive hardware, such as large collection optics or more powerful lasers to excite a larger return signal, can be used to compensate for this low sensitivity. However, even with more expensive hardware, the detection rate for very small particles is generally negligible, leading to an inability to detect aerosols composed of small particles (such as viruses), even if the particle number density is large. Even for large particles, a low detection rate can render sufficient data collection for a statistically meaningful detection (build-up of a particle count that is sufficient for agent detection) cumbersome and time-consuming. Second, only a small number of measurements can be made simultaneously. A small number of measurements implies a small number of histogram bins. This can result, in turn, in placing different particle types in the same histogram bin, leading to a high false alarm rate. Finally, the flow of particles near the large aperture collection optics of such systems can lead to fouling of the optics, thus lowering the optical efficiency of the system and driving up maintenance costs.
Accordingly, there is a need for enhanced methods and systems for detecting agents in a variety of backgrounds.